What is the purpose of Vertex AI Pipelines?
- To monitor model performance in production
- To store training datasets
- To orchestrate and automate ML workflows as directed acyclic graphs ✓
- To serve models as REST endpoints
Correct answer: To orchestrate and automate ML workflows as directed acyclic graphs
Option C is correct because Vertex AI Pipelines provides a managed service for defining, scheduling, and executing machine learning workflows as directed acyclic graphs (DAGs), allowing teams to automate and reproduce the full ML lifecycle from data preprocessing through training and evaluation. Option A describes Vertex AI Model Monitoring, which tracks data drift and prediction quality for deployed models. Option B describes Vertex AI datasets or Cloud Storage, which are the storage layer for training data, not the pipeline orchestration layer. Option D describes Vertex AI Endpoints or model serving infrastructure, which exposes trained models as REST APIs for online prediction.
Topic: · vertex ai pipelines, ml orchestration, dag, mlops